The Factor Content of Trade: Global trends since 1995

1. The Factor Content of Trade:Global trends since 1995 Abdul A. Erumban Marcel P. Timmer Gaaitzen J. de Vries University of Groningen WIOD conference, Vienna, 26-28 May 2010 This project is funded by the European Commission, Research Directorate General as part of the 7th Framework Programme, Theme 8: Socio-Economic Sciences and Humanities. Grant Agreement no: 225 281

2. Aim of this paper • Measure the factor content of imports and exports by country • Relevant for many important policy questions: • Who benefits from the stimulus package for car manufacturers in Europe? • Who is adding the ‘brains’ to electronic products, and is this changing over time? • Is a country upgrading the skill-content of its exports? Or which exported products see an increase in the skill-content?

3. Aim of this paper • Measure the factor content of tradefor • The 40 countries in WIOD • The period 1995-2006 Distinguish production factors: ICT and non-ICT capital, low-, medium-, and high-skilled employment Allow for trade in intermediate inputs Allow for differences in technology across countries (e.g. because of factor price differences)

4. Global production unbundling for the hard-disc drive

5. Related literature • Studies related to the effectiveness of import-substitution policies (e.g. Syrquin and Urata 1986 JDE; Chenery, Robinson, and Syrquin 1986) (as well as for projection and forecasting purposes) • Vertical specialization (Gourevitch 2000 WD; Hummels et al. 2001, JIE) • Factor content of trade, testing Heckscher-Ohlin-Vanek predictions (Dietzenbacher and van der Linden 1995 JRS; Davis and Weinstein 2001 AER; Reimer 2006 JIE; Johnson 2008; Trefler and Zhu 2010 JIE; Johnson and Noguera 2010 JIE; Feenstra and Hong 2007 NBER)

6. Data (1) • Data requirements to measure the factor content of trade: • By country for the period 1995-2006: • Supply and Use tables • AM, the N x N imported coefficient matrices • AD, the N x N domestic coefficient matrices • Bilateral trade data • WORLD KLEMS database • By country and industry for the period 1995-2006: • Capital compensation by industry • Low-, medium-, and high-skilled employment • PPPs (current version uses exchange rates)

7. Data (2) • Major data steps: • Obtain and harmonize official Supply and Use tables. • Benchmark SUTs on the national accounts and inter/extrapolate SUTs using the SUTRAS program (Temurshoev and Timmer 2010). • Construction of a KLEMS database for non-EU countries • Construction of global input-output matrix using imported coefficient matrix and bec classification

8. Methodology (1) • Net output of goods N for country C: yC= xC- AxC(1) where, yC is net output (NC x 1), xC is an (NC x 1) gross output vector, and A is an interregional input-output matrix of dimension (NC x NC) • Trade in goods: tC = yC – dC (2) where tC represents country C’s exports of goods (NC x 1) for intermediate or final use, and dC is demand for final use.

9. Methodology (2) • Define a total factor input matrix: • B* = B ( I – A)-1 (3) • Where B is a direct factor input matrix (F x NC), I an identity matrix, and B* the total factor input matrix. • The Measured Factor Content of Trade (MFCT) for country C is: • B*tC= B*yC – B*dC (4)

10. Results for the USA (1995)

11. Results for the USA (1995)

12. Results for the USA (1995)

13. USA and JAPAN (1995)

14. Concluding remarks • USA relatively large exporter of IT capital and high-skilled employment compared to Japan in 1995 • Much further data work is needed (interregional table for 40 WIOD countries, factor content for non-EU countries) • Measure factor content using volumes instead of values • Methodologically advance using price indices • Many applications for policy analysis appear feasible.

15. Additional material

16. Results for Japan (1995)

17. Results for Japan (1995)

18. Results for Japan (1995)